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Changes in sea ice conditions along the Arctic Northeast Passage from 1979 to 2012
Abstract
Sea ice conditions in the Arctic Northeast Passage (NEP) have changed dramatically in the last four decades, with important impacts on the environment and navigability. In the present study, multisource remote sensing data for 1979-2012 were analyzed to quantify seasonal, interannual, and spatial changes in sea ice conditions along the NEP. Data for October-November showed that spatially averaged ice thickness in the NEP decreased from 1.2-1.3. m in 2003-2006 to 0.2-0.6 m in 2011-2012. From 1979 to 2012, the fastest decreasing trend in monthly ice concentration occurred in October (-1.76% per year, P< 0.001), when the ice cover starts to increase. As a result of decreasing multiyear sea ice, thinning ice and delayed freeze-up, the spatially averaged length of open period (ice concentration < 50%) increased from 84. days in the 1980s to 114. days in the 2000s and reached 146 days in 2012. The Kara, Laptev, and East Siberian sectors were relatively inaccessible, especially the sector of 90-110°E around the Vilkitsky Strait. However, because of the thinning sea ice prior to the melt season and the enhanced positive polarity of the summer Arctic Dipole Anomaly, these sectors have become more accessible in recent years. The summer sea ice along the high-latitude sea route (HSR) north of the eastern Arctic islands, with a route distance comparable to the NEP, has also decreased during the last decade with the ice-free period reaching 42. days in 2012. The HSR avoids shallow waters along the coast, improving access to the Arctic sea route for deeper-draft vessels.
... The NEP is the shortest passage connecting Europe and Asia, which acts as a shortcut between the Pacific and Atlantic Ocean. A fully opened NEP would generate huge commercial and economic benefits by shortening the voyage between Asia, Europe and North America (Lei et al. 2015). In the summer of 2009, the vessels M/V Vision and M/V Friendship from Germany successfully crossed the entire NEP. ...
... Shibata et al. (2011) investigated the navigability of routes through the NEP as a function of sea ice concentration (SIC). The changes of sea ice conditions along the NEP from 1979 to 2012 were analyzed by Lei et al. (2015), which found the navigation period was shorter than expected. Yu et al. (2021) evaluated the influence of air temperature and surface wind on the SIC and determined the navigability of routes. ...
... The SIC threshold was set at 50% (Lei et al. 2015), while the SIT threshold is 30 cm (Liu et al. 2015). That is, regions where the SIC is less than or equal to 50% and the SIT is less than or equal to 30 cm are defined as navigable. ...
The decreasing of Arctic sea ice is projected to continue with global warming, which makes the summer navigation conditions of the Arctic improve. Based on the multi-source remote-sensing data with inter-sensor calibration processing and the ship-based observational data from R/V Xuelong and M/V Yongsheng, the sea ice conditions of the Arctic Northeast Passage (NEP) during the 2002–2021 summer seasons were analyzed, and the navigability of the NEP between July and October from 2002 to 2021 was discussed. Inter-sensor calibration could effectively reduce the deviation from different passive microwave data. Sea ice extent and thickness in the NEP decreased annually, which resulted in the navigability of the NEP showing a potential tendency toward improvement in navigability. The navigation period was mainly concentrated in early August to early October. The middle part of the NEP was primarily affected by sea ice. This influence decreased over time, while the navigation period increased, especially in the Vilkitsky Strait, which is a key shipping area. This analysis of sea ice conditions and navigability in the past 20 years could provide a reference for future scientific investigations and aid in merchant ship navigation in the Arctic summer.
... Over the period from 1979 to 2018, the 90-day safe navigation area for OW vessels expanded by 35% [22]. Ref. [23], through the analysis of ICE-Sat and CS2 sea ice condition data from 1979 to 2012, observed an increase in the open period of the NSR from 84 days in 1980 to 146 days in 2012 [23]. These results underscore the substantial uncertainty in the navigational windows of the NSR based on different SIT data. ...
... Over the period from 1979 to 2018, the 90-day safe navigation area for OW vessels expanded by 35% [22]. Ref. [23], through the analysis of ICE-Sat and CS2 sea ice condition data from 1979 to 2012, observed an increase in the open period of the NSR from 84 days in 1980 to 146 days in 2012 [23]. These results underscore the substantial uncertainty in the navigational windows of the NSR based on different SIT data. ...
With the accelerated melting of the Arctic sea ice, the opening of the Northern Sea Route (NSR) of the Arctic is becoming increasingly accessible. The purpose of this paper was to examine the impact of uncertainty in sea ice thickness (SIT) data on the opening of the NSR and to quantify the extent of this impact, which is essential to the regularized operation of polar shipping. A quantitative assessment framework was proposed to examine the influence of SIT data uncertainty on navigational uncertainty through three aspects: the navigational spatiotemporal windows, the distribution of safe sailing speeds, and the uncertainty in optimal route planning by employing four distinct SIT datasets. Furthermore, the sensitivity of navigational spatiotemporal windows, the distribution of safe sailing speeds, and route planning to variations in SIT were also evaluated. Results show that experiment results based on CS2SMOS exhibit a more aggressive profile, while results based on CPOM are more conservative. The difference in SIT data has a significant impact on the proportion of operations subject to special consideration areas, such as safety speed, sailing time, and distance in NEP. A 0.1 m discrepancy in sea ice thickness data results in an approximate 0.067 change in the proportion of operations within special consideration areas. This discrepancy also leads to an approximate speed change of 0.89 knots, a navigation duration change of approximately 4 days, and a distance change of 152 km within specified limits.
... The navigability of passages is affected by many factors, such as sea-ice conditions, meteorological and hydrological conditions, water depth, and local laws and regulations (Zhang et al., 2019). Nevertheless, sea ice is currently the greatest natural obstacle to navigation along the NSR (Lei et al., 2015;Rogers et al., 2013;Smith and Stephenson, 2013). Although the retreat of sea ice facilitates navigability of the Arctic, shipping is still hindered (Schøyen and Bråthen, 2011). ...
... In winter and spring, the NSR is typically plugged with thick sea ice (Cavalieri and Parkinson, 2012;Lei et al., 2015;Schr€ oder et al., 2019). Considering the threat from sea ice, Arctic transporters and LNG producers started to invest in vessels with stronger icebreaking capability. ...
Sea ice hinders the navigability of the Arctic, especially in winter and spring. However, three Arc7 ice-class Liquefied Natural Gas carrying vessels safely transited the Northern Sea Route (NSR) without icebreaker assistance in January 2021. More and more Arc7 ice-class vessels are putting into the transit services in the NSR. Therefore, it is necessary to analyze sea-ice conditions and their impact on navigation during wintertime, and the future navigability of Arc7 ice-class vessels along the NSR during winter and spring. Based on sea ice datasets from satellite observations and a model using data assimilation, we explored the sea-ice conditions and their impact during the first three successful commercial voyages through the NSR in winter. In addition, we analyzed the sea ice variation and estimated navigability for Arc7 ice-class vessels in the NSR from January to June of the years 2021–2050 using future projections of the sea-ice cover by the Coupled Model Inter-comparison Project Phase 6 (CMIP6) models under two emission scenarios (SSP2-4.5 and SSP5-8.5). The results reveal lower sea ice thickness and similar sea ice concentration during these three transits relative to the past 42 years (from 1979 to 2020). We found the thickness has a larger impact on the vessels’ speeds than sea ice concentration. Very likely sea ice thickness played a larger role than the sea ice concentration for the successful transit of the NSR in winter 2021. Future projections suggest sea ice thickness will decrease further in most regions of the NSR from January to June under all scenarios enabling increased navigability of the NSR for Arc7 ice-class vessels. Such vessels could transit through the NSR from January to June under all scenarios by 2050, while some areas near the coast of East Siberian Sea remain inaccessible for Arc7 ice-class vessels in spring (April and May). These findings can support the strategic planning of shipping along the NSR in winter and spring.
... Actually, the collection of various data from fields of meteorology, geophysics, oceanography, and floating ice is critical for the thorough risk assessment of shipping activities in the Arctic (Haimelin et al., 2017). For instance, satellite remote sensing data on sea ice extent, concentration, and thickness could not only be used to reveal the direct or indirect impacts of global climate change on the Arctic environment but could also help risk assessment for the shipping activities within the Arctic (Lei et al., 2015). ...
... It is reported that the Arctic sea ice extent reaches the minimum in September 2012 since 1979, with a reduction of 45% compared with the 1979−2010 climatology (Lei et al., 2015). Afterward, Arctic shipping gains increasing attention internationally, and, in practice, the number of ships transiting the Arctic waters increases by 25% from 2013 to 2019 (PAME, 2020). ...
The unique, ambiguous, and complex navigable environment determines the essential difference between Arctic shipping routes and conventional routes in regard to safety issues. To achieve a scientific understanding of the characteristics and variations of environmental risks involved in the Arctic shipping, it is essential to rationally address the uncertainty and incompleteness of environment‐related risk information. In this study, fuzzy evidential reasoning is introduced to carry out multisource heterogeneous data fusion and spatiotemporal dynamic assessment of navigable environmental risks for Arctic shipping routes. Based on big Earth data collected from the European Center for Medium‐Range Weather Forecasts, National Snow And Ice Data Center, National Center for Environmental Information, and University of Bremen from 2012 to 2019, a case study of the Northeast Passage is considered to demonstrate the feasibility of the proposed methodology. Finally, the results are described from three aspects: spatial distribution, temporal changes, and sensitivity analysis, with consideration of the entire passage and five marginal seas at the same time. Based on these findings, the prospect of application of big Earth data in risk assessment is further discussed from two aspects of knowledge acquisition by big data and risk analysis at different scales, to inspire sustainable development of Arctic shipping.
... Global warming has resulted in a massive reduction in icebound surface in the Arctic Ocean [5], and the Sea surface temperature increases each year [6]. According to research data from the National Oceanic and Atmospheric Administration (NOAA), arctic temperatures increased twice as fast as the global average in 2020 [7] which also means the rate of ice melt will become faster, and sea level will rise rapidly [8]. ...
... Marine CO 2 emissions = Fuel consumption * Emission Factor (5) The emission factor in this equation is based on the CO 2 emissions index released by the International Council on Clean Transportation (ICCT) in 2021. The emission factor of HFO was updated to 3.545 in 2021 [44]. ...
Maritime transportation is a key means for Taiwan to transport the cargo in the global trade. Global warming has led to two new navigation channels for arctic passages, the Northeast Passage and Northwest Passage. Research has increasingly addressed the unknown economic costs of these passages, and the increase of navigational activity in the Arctic Ocean has also resulted in CO2 emissions. Taiwan has one of the leading merchant fleets in the world; however, study on this aspect in Taiwan is not available. We use Port of Taipei, Taiwan as the starting place to compare the two arctic shipping routes and developed a model to determine the shipping costs and as well the CO2 emission. The results showed that a voyage from the Port of Taipei to the Port of Rotterdam through the Northeast Passage would be 2107 nautical miles shorter than voyage along the current sea route to Europe but 2% to 3% costlier; CO2 emissions would be 3% lower. Sailing to New York Harbor through the Northwest Passage would shorten voyages by 2459 nautical miles and reduce both costs and CO2 emissions by 7%. Therefore, if tolls were lowered or sailing speeds increased, sailing through the Arctic Passages could be a great opportunity for shipping industries and enable
Taiwan to develop its shipping economy while protecting the marine environment.
... In addition, snow depth is an essential variable for estimating sea ice thickness (Tilling, Andy, and Andrew 2016). Sea ice thickness observations in the warm season are the most valuable and beneficial to Arctic shipping and economic development (Dawson et al. 2022;Lei et al. 2015). Therefore, accurately estimating snow depth during warm seasons is pivotal for comprehending summer sea ice thickness, albedo feedback and fostering Arctic shipping development. ...
Summer snow plays an essential role in Arctic hydrology and in maintaining mass and energy balance of sea ice. However, there are great challenges in retrieving long‐term summer snow depths over Arctic sea ice. Here, we proposed a combined novel five‐variable long short‐term memory (hereafter CN5VLSTM) model based on brightness temperature data to yield warm‐season snow depth estimates. Then, year‐round snow depth estimates were obtained for the first time. The CN5VLSTM model and five additional snow depth methods were assessed during the warm season based on the ice mass balance buoy (IMB), Alfred Wegener Institute (AWI) snow buoy (AWI‐SB) and Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) snow buoy (MOSAiC‐SB). According to the three buoy products, the accuracy of the CN5VLSTM‐derived snow depth was highest among the five snow depth estimates with RMSEs of 10.2, 16.4, and 10.1 cm, respectively. Except for in May, the Arctic snow depth showed mainly a downward trend in warm months, and a significant downward trend was found in the Central Arctic. Excluding the Barents Sea, Kara Sea and Canadian Archipelago, the average year‐round snow depth decreased in the other subregions, and a significant negative trend was observed in the East Siberian and Chukchi Seas. Snowfall was an important factor that was related to the changes in snow depth in the East Siberian and Chukchi Seas. This study can provide new insights into the evolution characteristics of summer snow depth.
... At the time of writing, the NSR is ice-free for about three months a year, while the TSR is predicted to emerge by mid-century when the Central Arctic Ocean will become ice-free. 31 It has been reported that, between 2013 and 2019, the number of ships entering the Arctic grew by 25% and the distance they sailed in the region increased by 75%. 32 To cross the Arctic Ocean, vessels have to go through the territorial waters and EEZs of the Arctic Five, causing them unease over safety risks and threats to the marine environment. ...
... Located between the Beaufort Gyre and the Transpolar Drift, the East Siberian Sea influences Arctic sea ice characteristics through substantial sea ice movements, linked to long-term trends in Arctic atmospheric circulation (Colony and Thorndike 1984, Morris et al 1999, Soleymani and Scott 2023, Sumata et al 2023. The sea ice serves as a vital medium, impacting climate change, biogeochemical diversity, and the deposition of sediments and pollutants (Shakhova et al 2015, Krumpen et al 2019, Lee et al 2019, and notably affects the navigability of the Northeast Passage in spring (Lei et al 2015). The sensitivity of spring ice melt to storm tracks and the concurrent strong negative dynamical effect as the ice thins Su 2021, Anheuser et al 2022) highlight the need to focus on the dynamical change of sea ice in this region during melt period. ...
The change in sea ice thickness can be divided into dynamical and thermodynamical effect. In the last four decades, the drastic changes in multi-year ice thickness in East Siberian Sea during spring have made the sea ice more susceptible to dynamical effect. On one hand, the dynamical effect on sea ice in this region is the strongest, surpassing that of other Arctic marginal seas, and has been continuously strengthening since 1996. On the other hand, this region’s dynamical effect varies with the Central Arctic Index (CAI). An increase in CAI extreme positive phase years leads to more frequent occurrences of cyclonic circulation anomalies, favoring the development of dynamical effect in spring East Siberian Sea. Furthermore, the influence of 10 m wind field on dynamical effect has shifted from being dominated by the northward component (v) to a combined effect of both northward and eastward components (v and u). This change is a result of alteration in the response pattern of wind field to CAI across the interdecadal periods.
... Many studies have been conducted to assess the NP (called the sailing season) in the Arctic, some of which have focused on historical changes with satellite observations. For example, Lei et al. (2015) assessed shipping periods for the NEP from 1979 to 2012 by using three ice concentration thresholds. Their research showed that the spatially averaged length of the open period (ice concentration <50%) increased from 84 days in the 1980s to 114 days in the 2000s and reached 146 days in 2012. ...
The Northeast Passage (NEP) holds immense potential as a link for maritime transport activities between Europe and Asia, primarily due to the extended sailing season resulting from global warming. However, the economic viability of the Arctic shipping route remains disputed. This study aims to comprehensively evaluate the feasibility of container transportation along the NEP compared to that along the Suez Canal Route (SCR) by using current (2021–2023) and future (2025–2065) scenarios. The results reveal that larger vessels have lower CO2 emissions and costs than small vessels in the NEP, but the costs for larger vessels in the NEP are still higher than those in the SCR throughout both summer and winter seasons under the current scenario. The outcomes also show that a progressive carbon tax scheme will increase the unit shipping costs for all routes in the future scenario, with the NEP being most economically viable during summer. Furthermore, the extended navigable period (NP) bolsters the NEP’s economic cost advantage during a seasonal period. Nevertheless, from a year-round operations standpoint, the NEP remains less competitive than the SCR before 2065. The conclusions drawn from this research serve as a significant resource for decision-makers when formulating operational plans.
... August temperatures in this region rose at a rate of 0.7 °C per decade from 1982 to 2017. Lei et al. 11 and Wang et al., 12 investigated the changes in sea ice conditions along the Arctic Northeast Passage over the past four decades. Their analysis of remote sensing data from 1979 to 2012 reveals a significant decrease in Arctic ...
Climate change has been inducing a continuous increase in temperatures within the Arctic region, consequently leading to an escalation in the rates of Arctic ice depletion. These changes have profound implications for navigation along the Arctic Northern Sea Route (NSR). However, access to the NSR is constrained to specific temporal intervals when the sea ice thickness reaches a threshold that permits safe passage of ships. This research employs climate change model simulations and the Polar Operational Limit Assessment Risk Indexing System framework to investigate the navigational feasibility of diverse ship types along NSR during the calendar years 2030, 2040, and 2050, under SSP2-4.5 and SSP5-8.5 scenarios. Different ship categories were analyzed within the context of these two scenarios. Results indicate considerable variation in the navigability of different ship categories across different scenarios and years. In general, polar ships demonstrate a higher navigational potential throughout most of the year, while pleasure crafts are constrained to specific periods. These findings bear significant implications for the future of shipping along the NSR. As Arctic ice continues to melt, NSR is anticipated to become more accessible to ships, albeit with navigational availability remaining contingent on the ship category and seasonal considerations.
... In stark contrast, the Arctic, located in the densely populated Northern Hemisphere, has borne the brunt of significant human-induced impacts. Amid the backdrop of global climate change, the Arctic has been identified as the region sustaining the most pronounced temperature increases, accompanied by a considerable annual decrease in sea ice volume [20][21][22][23][24][25][26]. Particularly noteworthy is the accelerating decline in Arctic sea ice extent during the Northern Hemisphere's summer and autumn, characterized by an extended melting period and diminishing long-term ice coverage [23,27]. ...
The 44 years (1979–2022) of satellite-derived sea ice extent in the Arctic and Antarctic reveals the details and new trends in the process of polar sea ice coverage changes. The speed of Arctic sea ice extent reduction and the interannual difference significantly increased after 2004. Trend analysis suggests that the Arctic Ocean may experience an ice-free period around 2060. The maximum anomaly of Arctic sea ice extent has gradually transitioned from September to October, indicating a trend of prolonged melting period. The center of gravity of sea ice in the Arctic Ocean is biased towards the Pacific side, and the spatial distribution pattern of sea ice is greatly influenced by the Atlantic warm current. The dynamism of the sea ice extent on the Atlantic side is significantly greater than in other regions. Since 2014, the Antarctic sea ice extent has shifted from slow growth to a rapid decreasing trend; the sea ice extent reached a historical minimum in 2022, decreasing by 2.02 × 106 km2 compared to 2014. The Antarctic experiences seven months of ice growth each year and five months of ice melting period, the annual change patterns of sea ice extent in the Arctic and Antarctic are slightly different.
... the Arctic Northeast Passage (NEP) has undergone remarkable changes in sea ice conditions, significantly impacting both the environment and navigational capabilities [166]. Research indicates a continued reduction in Arctic sea ice, leading to the shortening of trade routes in the Arctic Ocean and potentially affecting the global economy [167]. ...
The deep learning, which is a dominating technique in artificial intelligence, has completely changed the image understanding over the past decade. As a consequence, the sea ice extraction (SIE) problem has reached a new era. We present a comprehensive review of four important aspects of SIE, including algorithms, datasets, applications, and the future trends. Our review focuses on researches published from 2016 to the present, with a specific focus on deep learning-based approaches in the last five years. We divided all relegated algorithms into 3 categories, including classical image segmentation approach, machine learning-based approach and deep learning-based methods. We reviewed the accessible ice datasets including SAR-based datasets, the optical-based datasets and others. The applications are presented in 4 aspects including climate research, navigation, geographic information systems (GIS) production and others. It also provides insightful observations and inspiring future research directions.
... Along with reduced sea ice cover in both extent and thickness (Kwok and Rothrock, 2009;Cavalieri and Parkinson, 2012), the proportion of multiyear ice is decreasing (Maslanik et al., 2007;Nghiem et al., 2007), and the duration of open water is extending (Stroeve et al., 2014;Dong et al., 2021). The continued sea ice loss will make the Arctic Ocean increasingly more accessible for oil and natural gas exploration, marine transport, tourism, and other economic activities (Lei et al., 2015;Pizzolato et al., 2016). On the other hand, thinner and more fragile sea ice has important implications for Arctic marine ecosystems, weather, and climate (Honda et al., 2009;Francis and Vavrus, 2012). ...
Satellite records show that the extent and thickness of sea ice in the Arctic Ocean have significantly decreased since the early 1970s. The prediction of sea ice is highly important, but accurate simulation of sea ice variations remains highly challenging. For improving model performance, sensitivity experiments were conducted using the coupled ocean and sea ice model (NEMO-LIM), and the simulation results were compared against satellite observations. Moreover, the contribution ratios of dynamic and thermodynamic processes to sea ice variations were analyzed. The results showed that the performance of the model in reconstructing the spatial distribution of Arctic sea ice is highly sensitive to ice strength decay constant (Crhg). By reducing the Crhg constant, the sea ice compressive strength increases, leading to improved simulated sea ice states. The contribution of thermodynamic processes to sea ice melting was reduced due to less deformation and fracture of sea ice with increased compressive strength. Meanwhile, dynamic processes constrained more sea ice to the central Arctic Ocean and contributed to the increases in ice concentration, reducing the simulation bias in the central Arctic Ocean in summer. The RMSE between modeled and the CryoSat-2/SMOS satellite observed ice thickness was reduced in the compressive strength-enhanced model solution. The ice thickness, especially of multiyear thick ice, was also reduced and matched with the satellite observation better in the freezing season. These provide an essential foundation on exploring the response of the marine ecosystem and biogeochemical cycling to sea ice changes.
... Nevertheless, only a few studies have analyzed the historic navigability in the NEP by using sea ice data (e.g., Lei et al., 2015;Ji et al., 2021;Yu et al., 2021;Cao et al., 2022). The seaworthiness of the whole Arctic Ocean has been assessed in a recent study with the usage of a Combined Model and Satellite Thickness (CMST) data set, but it is limited from 2011 to 2016 and the long-term tendency is thus still lacking (Zhou et al., 2021). ...
Sea ice, one of the most dominant barriers to Arctic shipping, has decreased dramatically over the past four decades. Arctic maritime transport is hereupon growing in recent years. To produce a long-term assessment of trans-Arctic accessibility, we systematically revisit the daily Arctic navigability with a view to the combined effects of sea ice thickness and concentration throughout the period 1979–2020. The general trends of Navigable Windows (NW) in the Northeast Passage show that the number of navigable days is steadily growing and reached 89±16 days for Open Water (OW) ships and 163±19 days for Polar Class 6 (PC6) ships in the 2010s, despite high interannual and interdecadal variability in the NWs. More consecutive NWs have emerged annually for both OW ships and PC6 ships since 2005 because of the faster sea ice retreat. Since the 1980s, the number of simulated Arctic routes has continuously increased, and optimal navigability exists in these years of record-low sea ice extent (e.g., 2012 and 2020). Summertime navigability in the East Siberian and Laptev Seas, on the other hand, varies dramatically due to changing sea ice conditions. This systematic assessment of Arctic navigability provides a reference for better projecting the future trans-Arctic shipping routes.
... Smith et al. [9] used the Arctic September sea ice concentration and thickness data to analyze the climate prediction model of sea ice characteristics, thereby obtaining the Arctic optimal sailing route. Lei et al. [10] used remote sensing data from 1979 to 2012 to analyze the temporal and spatial changes of sea ice in the NEP, and found that the sea ice thickness of the NEP decreased by 0.7-1.0 m in the past 10 years, and the opening period of the NEP also increased. ...
Climate warming has enabled the Arctic region to achieve seasonal navigation, and sea ice concentration is an important factor affecting the navigation of the Arctic waterways. This article uses the Arctic sea ice concentration data of the three highest temperatures in 2016, 2019, and 2020, combined with the Arctic summer sea level pressure, wind field, temperature, temperature anomaly, ice age, and sea ice movement data to analyze the spatial and temporal variation of sea ice and connectivity in the Northeast Passage (NEP) of the Arctic in Summer in three hot years, and summarizes the causes of sea ice anomalies. The results show that: (1) the summer Arctic sea ice extent in 2016, 2019 and 2020 were all lower than the multi-year average sea ice extent, and the summer sea ice extent in 2020 had the largest change trend; (2) in October of these three years, the sea ice was all negative anomalies, extending the opening time of the NEP; (3) when the sea ice concentration was 30% as the threshold, the navigation period of the NEP in 2016 was from mid-August to late October, 2019 was from the beginning of August to mid-October, 2020 was from the end of July to the end of October, and 2020 was the longest year since the opening of the NEP; (4) when the sea ice concentration was 10% as the threshold, the navigation period of the NEP in 2016 was from the end of August to the end of October, 2019 was from early August to mid-October, and 2020 was from the beginning of August to the end of October; (5) the key navigable areas of the NEP in the past three years were the central waters of the East Siberian Sea, the New Siberian Islands and the Vilkitsky Strait; (6) the navigation period of the NEP in 2016, 2019 and 2020 was longer. The main reasons were that the temperature of the NEP in the past 3 years was relatively high, the wind was weak, the sea ice movement had little effect, and the sea ice age in the key navigable areas was first year ice, which was easy to melt, which greatly promoted the opening of the NEP.
... Some studies evaluate the feasibility of NEP or NSR based on microwave radiometer observation of SIC and SIT. Lei et al. (2015) found that the spatially averaged open period in the NEP, defined by a 50% SIC threshold, is approximately doubled from the early 1980s (∼ 70 days) to the early 2010s (∼ 140 days). While these studies generally consider only sea ice condition as the critical factor for the evaluation of navigability in the NEP or NSR, Chen et al. (2019) applied the Arctic Transport Accessibility Model (ATAM) for the analysis of navigation risk, which integrates both the radiometer-derived SIC and SIT information and vessel types. ...
The rapid decline of Arctic sea ice has been reminding us the significant impacts caused by global warming. However, the other side of the coin is that this opens a window to utilize the Arctic sea routes in the summer seasons, bringing remarkable economic benefits for ocean transportation between Asia and Europe. However, commercial vessels with low ice classes must tackle substantial environmental challenges in the Arctic sea routes, particularly those caused by variable sea ice, even in the melting seasons. Therefore, the science-based support for shipping safety in the Arctic sea routes is being given more prominence. Emerging satellite remote sensing technology plays a critical role in environmental monitoring in the Arctic. This paper reviews state-of-the-art satellite observations on monitoring sea ice and potential applications on supporting shipping activities in the Arctic Ocean. Moreover, we introduced a recently developed system based on satellite observations to support the safe transportation of Chinese cargo vessels in the Arctic northern sea route, demonstrating the efforts by both the science and business communities to promote the development of the polar silk road.
... Fast ice also hinders the navigation of Arctic sea routes. The feasibility of Arctic shipping depends on the timing of LFSI breakup in key channels (Lei et al., 2015). Therefore, understanding of the annual cycle of LFSI is crucial for both scientific and economic purposes. ...
... The Northwest Passage can therefore bring greater benefits than the Panama Canal in terms of sailing distance, time, and cost (Haas and Howell, 2015). The spatially-averaged length of its open period increased to 114 days in the 2000 s and reached 146 days in 2012 (Lei et al., 2015). Observational evidence has also shown that the average navigable period of the Northern Sea Route for normal merchant ships was extended to October 24 from 2010 to 2017 (Chen et al., 2019). ...
Although a rapid decrease in sea ice due to global warming has improved the navigable potential of the Arctic passages, the extent to which this area will become viable for commercial shipping in the future remains unclear. This study investigated the accessibility of the Northern Sea Route and Northwest Passage under global warming of 2°C and 3°C. We applied the Polar Operational Limit Assessment Risk Indexing System to measure navigability by considering the impacts of sea ice and ice resistance of ships. Except for the Parry Channel, surface air temperature is positive in the Seas along two passages in September under 2℃ warming. With global warming of 3°C, the warming area extends northward, and the concentration of sea ice drops below 20%. The thickness of the sea ice is still substantial in the eastern Beaufort Sea and the waters within the Canadian Arctic Archipelago and north of Greenland, both of which can restricting the opening of the Arctic passages. Temperature increases cause sea ice to be younger and are more pronounced in the seas on the European side of the Arctic. The results indicate that changes in sea ice improve the navigability of the Arctic passages. Ships in Polar Class 6 may be unimpeded along two Arctic passages in November from 2℃ warming onward, whereas ordinary ships may be capable of passing the Northern Sea Route with global warming of 3℃, with maximum potential in September. This study provides an important reference for planning global shipping in the Arctic in the future, even with some uncertainty in the model projections.
... It is well known that the global climate change is affecting the Arctic ice layers [1,2,3,4]. In general, the ice layer formations are much different than those which were studied in early acoustic experiments. ...
Arctic acoustics have been of concern in recent years for the US navy. First-year ice is now the prevalent factor in ice coverage in the Arctic, which changes the previously understood acoustic properties. Due to the ice melting each year, anthropogenic sources in the Arctic region are more common: military exercises, shipping, and tourism. For the navy, it is of interest to detect, classify, localize, and track these sources to have situational awareness of these surroundings. Because the sources are on-water or on-ice, acoustic radiation propagates at a longer distance and so acoustics are the method by which the sources are detected, classified, localized, and tracked. These methods are all part of sound navigation and ranging (SONAR). This dissertation describes algorithms which will better SONAR results without modification of the sensors or the environment and the process by which to arrive to this point. The focus is to use supervised machine learning algorithms to facilitate such technological enhancements. Specifically, neural networks analyze labeled experimental data from a first-year, shore-fast, shallow and narrow water environment. The experiments were conducted over the span of three years from 2019 to 2022, mostly during the months from January to March where ice formed over the Keweenaw Waterway at the Michigan Technological University. All experiments were conducted to analyze a passive acoustic source; that is, the source was non-cooperative and did not send any localizing pings for active SONAR. The experiments were recorded using an underwater pa-type acoustic vector sensor (AVS). The data and analysis were done intermittently to update any upcoming experiments with discrepancies found in the analysis to create a more generalized algorithm. The work in this dissertation focuses on two topics for passive SONAR: localization and classification. Because of the ``black box" nature in machine learning, tracking the target source is an extension of localization and thought of as the same goal within machine learning. To introduce and verify the complexity of the testing environment, an underwater acoustic simulation is shown with Ray tracing and bathymetry data to compare with the experimental results used in machine learning. The focus of the algorithms is to produce the best results for the experiments and compare the results with traditional methods, such as a simulation or a linear Gaussian localization with a Kalman filter. Experiments studying neural network types have shown that the Vision Transformer (ViT) produces excellent results. The ViT is capable of analyzing acoustic intensity azimuthal spectrogram (azigram) data and localizing a moving target at high accuracy, and the ViT is capable of classifying multiple acoustic sources with the acoustic intensity magnitude spectrogram at high accuracy as well.
... There is a strong coupling between sea ice and climate, studying SIM can help us understand and predict climate change in the polar regions or even on a global scale (Vaughan et al., 2013). SIM affects sea ice mass balance (Smedsrud et al., 2017), shipping safety (Lei et al., 2015;Wu et al., 2021) and ecosystems (Pfirman et al., 1999) in polar regions. In addition, accurate and detailed information on SIM is the basis for accurate assessment of sea ice fluxes and study of sea ice dynamics characteristics, and is an important input parameter for sea ice model simulations. ...
This study presents an improved, versatile, and efficient algorithm based on the Oriented FAST and Rotated BRIEF (ORB) combined with the maximum cross-correlation (MCC) (ORB-MCC) for extracting sea ice motion (SIM) vectors. Quadtree ORB (Q-ORB) extracts more uniform feature points than ORB (uniformity is 3 times higher) and eliminates the concentration of ORB-extracted feature points on ice ridges, leads and coastlines, thereby providing excellent initial conditions for MCC calculations. In addition, a geographic grid-based matching (GGM) algorithm is developed to replace the brute-force matching algorithm (BFM). GGM is 8–10 times more efficient for matching feature points than BFM, thereby increasing the computational efficiency of extracting SIM vectors. Moreover, a locally consistent (LC) flow field filtering process is incorporated to facilitate the filtering of the SIM field. Combining cross-correlation-coefficient-threshold (CCCT)-based and LC filtering processes eliminates erroneous vectors more efficiently than using a CCCT-based filtering process alone. The improved algorithm, named Q-ORB-MCC, is used to extract SIM vectors from imagery acquired by the Sentinel-1 Synthetic-Aperture Radar (SAR), Envisat Advanced SAR (ASAR), Phased Array type L-band SAR-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), and Moderate Resolution Imaging Spectroradiometer (MODIS). An analysis of the accuracy and effectiveness of the extracted SIM vectors shows that Q-ORB-MCC extracted SIM vectors from Sentinel-1, ASAR, and MODIS images with 4%, 253%, and 62% higher accuracy than ORB-MCC, respectively. Meanwhile Q-ORB-MCC could obtain more SIM vectors from Sentinel-1 and ASAR images.
... Several studies have been conducted to determine historical changes in navigability along the trans-Arctic routes (Khon et al., 2017;Lei et al., 2015;Yu et al., 2020). However, due to the lack of long-term highquality sea ice thickness (SIT) data, the key characteristics for determining the navigability of the routes, including the navigation season (NS, start, end, and length), the safety shipping area (SSA), and the location of the shortest navigable route, have rarely been determined or analyzed over a long-term period. ...
Rapid declines in Arctic sea ice coverage over the past four decades have increased the commercial feasibility of trans-Arctic routes. However, the historical changes in navigability of trans-Arctic routes remain unclear, and projections by global circulation models (GCMs) contain large uncertainties since they cannot simulate long-term Arctic sea ice changes. In this study, we determined the changes in trans-Arctic routes from 1979 to 2019 by combining two harmonized high-quality daily sea ice products. We found that the trans-Arctic routes are becoming navigable much faster than projected by the GCMs. The navigation season for open water (OW) vessels along the Northeast Passage (NEP) has lengthened from occasionally navigable in the 1980 s to 92 ± 15 days in the 2010 s. In contrast, previous GCM projections have suggested that navigability would not be achieved until the mid-21st century. The 90-day safety shipping area for OW vessels expanded by 35% during 1979–2018, reaching 8.28 million km² in 2018, indicating an increasing rate of 0.08 ± 0.01 million km² per year. The shortest trans-Arctic routes were also shifted further north than the model projections. Regular ships have been able to safely travel north along the islands in the NEP and transit through the M’Clure Strait in the Canadian Arctic Archipelago during the 2010 s, while previous studies have projected that this would not be feasible until the mid-21st century. We also found that the improved navigability of trans-Arctic routes enables commercial ships to transport approximately 33–66% (at the same load factor) more goods from East Asia to Europe during the Arctic shipping season than by the traditional Suez Canal route. These findings highlight the need for aggressive actions to develop mandatory rules that promote navigation safety and strengthen environmental protection in the Arctic.
... Lei et al. assessed open shipping periods for the Arctic NEP from 1979 to 2012 using three ice concentration thresholds of 75%, 50%, and 15%. Their research showed that the spatially averaged length of the open period (ice concentration <50%) increased from 84 days in the 1980s to 114 days in the 2000s and reached 146 days in 2012 (Lei et al., 2015). Pizzolato et al. quantified the spatial relationships between shipping activity and sea concentration within the Canadian Arctic over a 26-year period from 1990 to 2015 and indicated that increases in shipping activity are significantly correlated with reductions in sea ice concentration in regions of the Beaufort Sea, Western Parry Channel, Western Baffin Bay, and Foxe Basin (Pizzolato, Howell, Dawson, Laliberté, & Copland, 2016). ...
Research on Arctic passages has mainly focused on navigation policies, sea ice extraction models, and navigation of Arctic sea routes. It is difficult to quantitatively address the specific problems encountered by ships sailing in the Arctic in real time through traditional manual approaches. Additionally, existing sea ice information service systems focus on data sharing and lack online calculation and analysis capabilities, making it difficult for decision-makers to derive valuable information from massive amounts of data. To improve navigation analysis through intelligent information service, we built an advanced Ship Navigation Information Service System (SNISS) using a 3D geographic information system (GIS) based on big Earth data. The SNISS includes two main features: (1) heuristic algorithms were developed to identify the optimal navigation route of the Arctic Northeast Passage (NEP) from a macroscale perspective for the past 10 years to the next 100 years, and (2) for key sea straits along the NEP, online local sea-ice images can be retrieved to provide a fully automatic sea ice data processing workflow, solving the problems of poor flexibility and low availability of real sea ice remote sensing data extraction. This work can potentially enhance the safety of shipping navigation along the NEP.
... Against the background of global warming, recent studies have clearly shown that the Arctic multi-year sea ice extent, thickness, and the fraction of multi-year ice have decreased significantly [1][2][3][4][5][6]. In addition, the length of the melt season has increased at 5-10 days per decade since 1978 when satellite remote sensing began to be widely used for Arctic sea ice monitoring [7]. ...
As a long-term, near real-time, and widely used satellite derived product, the summer performance of the Special Sensor Microwave Imager/Sounder (SSMIS)-based sea ice concentration (SIC) is commonly doubted when extensive melt ponds exist on the ice surface. In this study, three SSMIS-based SIC products were assessed using ship-based SIC and melt pond fraction (MPF) observations from 60 Arctic cruises conducted by the Ice Watch Program and the Chinese Icebreaker Xuelong I/II. The results indicate that the product using the NASA Team (SSMIS-NT) algorithm and the product released by the Ocean and Sea Ice Satellite Application Facility (SSMIS-OS) underestimated the SIC by 15% and 7–9%, respectively, which mainly occurred in the high concentration rages, such as 80–100%, while the product using the Bootstrap (SSMIS-BT) algorithm overestimated the SIC by 3–4%, usually misestimating 80% < SIC < 100% as 100%. The MPF affected the SIC biases. For the high MPF case (e.g., 50%), the estimated biases for the three products increased to 20% (SSMIS-NT), 7% (SSMIS-BT), and 20% (SSMIS-OS) due to the influence of MPF. The relationship between the SIC biases and the MPF observations established in this study was demonstrated to greatly improve the accuracy of the 2D SIC distributions, which are useful references for model assimilation, algorithm improvement, and error analysis.
... Peeken and others, 2018; Krumpen and others, 2020). Outlying islands (e.g. the New Siberian Islands) are crucial nodes affecting the accessibility of the Northeast Passage ( Lei and others, 2015). Ice formation in the peripheral seas around these islands is affected by the local shoreline and bathymetry, which can lead to further northward protrusion of the LFSI edge. ...
Arctic landfast sea ice (LFSI) represents an important quasi-stationary coastal zone. Its evolution is determined by the regional climate and bathymetry. This study investigated the seasonal cycle and interannual variations of LFSI along the northwest coast of Kotelny Island. Initial freezing, rapid ice formation, stable and decay stages were identified in the seasonal cycle based on application of the visual inspection approach (VIA) to MODIS/Envisat imagery and results from a thermodynamic snow/ice model. The modeled annual maximum ice thickness in 1995–2014 was 2.02 ± 0.12 m showing a trend of −0.13 m decade−1. Shortened ice season length (−22 d decade−1) from model results associated with substantial spring (2.3°C decade−1) and fall (1.9°C decade−1) warming. LFSI break-up resulted from combined fracturing and melting, and the local spatiotemporal patterns of break-up were associated with the irregular bathymetry. Melting dominated the LFSI break-up in the nearshore sheltered area, and the ice thickness decreased to an average of 0.50 m before the LFSI disappeared. For the LFSI adjacent to drift ice, fracturing was the dominant process and the average ice thickness was 1.56 m at the occurrence of the fracturing. The LFSI stages detected by VIA were supported by the model results.
... The Siberian coast is a key region in the Arctic Ocean for ship navigation through the Northeast Passage (Lei et al., 2015). A wide continental shelf exists in the East Siberian Sea and Chukchi Sea. ...
As a key region of Northeast Passage, the polynya along the Siberian coast in the East Siberian and Chukchi Seas is important to local dynamic and thermodynamic processes, sea ice production and marine ecosystem. The detailed variations of polynya and the contributions of atmospheric and oceanic factors to the polynya have not been explored quantitatively. AMSR-E satellite data from January to April during the period 2003–2011 were used to study the impacts of wind stress and ocean heat transport on variations of polynya in the East Siberian Sea and Chukchi Sea. The study region was divided into six domains. Four sets of AMSR-E data with resolutions of 6.25 km and 12.5 km were compared based on two algorithms of sea ice concentration (referred to as 6.25 km-IC and 12.5 km-IC) and sea ice thickness (referred to as 6.25 km-h and 12.5 km-h). The monthly and yearly polynya areas in the four cases and six domains had remarkable differences. The two cases of 6.25 km-h and 12.5 km-h had larger areas of polynya than the other two cases of 6.25 km-IC and 12.5 km-IC. The difference in polynya area between the 6.25 km-h and 12.5 km-h cases was much smaller than the difference between the 6.25 km-IC and 12.5 km-IC cases. The study of atmospheric and oceanic mechanisms on polynya is influenced significantly by the sensitivity of polynya areas. In general, the impact of wind stress and ocean heat transport on the polynyas had noticeable monthly and interannual variations and was dependent on the locations of the polynyas. The alongshore and offshore wind had stronger correlations with the polynya area than ocean heat transport. Although the higher resolution (6.25 km) AMSR-E data are best for the study of atmospheric and oceanic impacts on polynya area, the coarse resolution (12.5 km) AMSR-E data based on sea ice thickness can also be used. Wind direction dominated the polynya area in the East Siberian Sea and wind speed dominated the polynya area in the Chukchi Sea. The variation in ocean heat transport was influenced mainly by variation in volume transport rather than variation in water temperature.
... In a warmer Arctic, the NEP is more likely to be open for transportation and resource exploitation. Between the LS and the ESS, where relatively inaccessible ice blocks along the NEP are found (Lei et al., 2015), we identify the phenomenon of the MOS. ...
Ice/snow melt onset (MO) is critical timing for ice‐albedo positive feedback in the Arctic. For 1979–1998, the MO in the East Siberian Sea (ESS) occurred earlier than in the Laptev Sea (LS) for 12 of 20 years. However, for 1999–2018, the LS experienced significantly earlier MO than the ESS for 8 of 20 years. We referred to this phenomenon as the MO Seesaw (MOS) and quantified it by the MO difference between the LS and ESS. The MOS is more pronounced since 1999. For positive MOS, storm tracks in May are located south of the ESS and easterly wind prevails, resulting in higher surface air temperature and total‐column water vapor and, therefore, earlier MO in the ESS. For negative MOS, storm tracks are located southwest of the LS, and strong southerly/southwesterly winds bring warm air from coastal land toward the LS. When low pressure is centered over the Barents Sea in April, sea ice in the LS has driven away from the coasts, which increases the surface latent heat flux and humidifies the overlying atmosphere, and eventually leads to earlier MO in the LS. Both the local variables and the large‐scale atmospheric circulation indices were more related to the MOS for 1999–2018 than for 1979–1998.
... Rodrigues [12] used sea ice concentration data from 1979 to 2007 to study the sea ice coverage and the length of the ice-free season in the Arctic marginal area. Ruibo et al. [13] used remote sensing data from 1979 to 2012 to study the interannual and seasonal spatial variations of sea ice in the Northwest Passage (NWP), and found that the navigation period of the NWP increased by 32 days in 32 years. Dawei et al. [14] used NSIDC sea ice products to study the kinematic characteristics of sea ice in the Arctic Fram Strait and the northern part of the NEP. ...
The ablation of Arctic sea ice makes seasonal navigation possible in the Arctic region, which accounted for the apparent influence of sea ice concentration in the navigation of the Arctic route. This paper uses Arctic sea ice concentration daily data from January 1, 2000, to December 31, 2019. We used a sea ice concentration threshold value of 40% to define the time window for navigating through the Arctic Northeast Passage (NEP). In addition, for the year when the navigation time of the NEP is relatively abnormal, we combined with wind field, temperature, temperature anomaly, sea ice age and sea ice movement data to analyze the sea ice conditions of the NEP and obtain the main factors affecting the navigation of the NEP. The results reveal the following: (1) The sea ice concentration of the NEP varies greatly seasonally. The best month for navigation is September. The opening time of the NEP varies from late July to early September, the end of navigation is concentrated in mid-October, and the navigation time is basically maintained at more than 30 days. (2) The NEP was not navigable in 2000, 2001, 2003 and 2004. The main factors are the high amount of multi-year ice, low temperature and the wind field blowing towards the Vilkitsky Strait and sea ice movement. The navigation time in 2012, 2015 and 2019 was longer, and the driving factors were the high temperature, weak wind and low amount of one-year ice. The navigation time in 2003, 2007 and 2013 was shorter, and the influencing factors were the strong wind field blowing towards the Vilkitsky Strait. (3) The key navigable areas of the NEP are the central part of the East Siberian Sea and the Vilkitsky Strait, and the Vilkitsky Strait has a greater impact on the NEP than the central part of the East Siberian Sea. The main reason for the high concentration of sea ice in the central part of the East Siberian Sea (2000 and 2001) was the large amount of multi-year ice. The main reason for the high concentration of sea ice in the Vilkitsky Strait (2000 to 2004 and 2007, 2013) was the strong offshore wind in summer, all of which were above 4 m s−1, pushing the sea ice near the Vilkitsky Strait to accumulate in the strait, thus affecting the opening of the NEP.
... Severe winters, snowstorms and low-temperature events have occurred frequently in the mid-high latitudes of Eurasia (Seager et al. 2010, Wu et al. 2014, Luo et al. 2019, playing a vital role in the intensity, persistence and region of occurrence of Ural Blocking ). In addition to negative effects, the loss of sea ice contributes to the development of transportation along the northern sea routes and to increases in net primary productivity (Lei et al. 2015, Li et al. 2019a). ...
Summer Arctic cyclones occur frequently in the Arctic Ocean and play an important role in sea ice variability. We used a reanalysis dataset and sea ice concentration data to identify and track summer great Arctic cyclones and to quantitatively analyse the contribution of cyclones to variations in sea ice concentration and area. We further explored the process of how cyclones influence sea ice via sea surface temperature, radiation, sea ice motion and ice deformation. The results indicate that cyclones accelerate decreases in sea ice concentration and area. The higher the values of the sea ice concentration index (ratio of maximum variation in sea ice concentration change rate to the minimum value of sea ice concentration change rate caused by the cyclone) and sea ice area responsivity (ratio of sea ice area change caused by cyclones to total sea ice area change) are, the greater is the contribution of cyclones to sea ice reduction. Over time, sea ice concentration decreases, and the impacts of cyclones on sea ice concentration are enhanced. During summer great cyclones, a strong low-pressure system and wind stress lead to increases in sea ice motion, ice divergence and changes in sea surface temperature and net radiation, promoting decreases in sea ice concentration and area. This study aids in the prediction of short-term sea ice change, and is beneficial to the development of coupled atmosphere-ocean-ice models.
... Smith et al. 34 also used 80% as the "outer ice-free period" but called 15% the "open period". We highlight 15% here because of its frequent use 30,31,64 and suitability for transit by open-water vessels 65 . Results for 80% show longer open-water periods but similar biases, trends, and sensitivity to temperature (Supplementary Figs. ...
The shrinking of Arctic-wide September sea ice extent is often cited as an indicator of modern climate change; however, the timing of seasonal sea ice retreat/advance and the length of the open-water period are often more relevant to stakeholders working at regional and local scales. Here we highlight changes in regional open-water periods at multiple warming thresholds. We show that, in the latest generation of models from the Coupled Model Intercomparison Project (CMIP6), the open-water period lengthens by 63 days on average with 2°C of global warming above the 1850-1900 average, and by over 90 days in several Arctic seas. Nearly the entire Arctic, including the Transpolar Sea Route, has at least 3 months of open water per year with 3.5°C warming, and at least 6 months with 5°C warming. Model bias compared to satellite data suggests that even such dramatic projections may be conservative.
... Therefore, their forecasts and applications to navigation support are very important for the development of Arctic shipping (Inoue, 2020). Sea ice, which has a large and complicated spatiotemporal variability (Lei et al., 2015). At present, there is a lack of long-term and continuous observation network for the Arctic marine environment, especially for sea ice, which is a grand challenge for the utilization of the Arctic sea routes. ...
As Arctic sea ice continues to melt and global demand for clean energy rises, Russia’s Liquefied Natural Gas (LNG) exports via the Northern Sea Route (NSR) are rapidly increasing. To ensure the operational safety of LNG carriers and safeguard the economic interests of stakeholders, including shipowners, a thorough assessment of the navigability of various ice-class LNG carriers along this route is essential. This study collected Arctic ice condition data from 2014 to 2023 and applied the Polar Operational Limit Assessment Risk Indexing System (POLARIS) methodology to calculate the Risk Index Outcome (RIO) for LNG carriers with No Ice Class, Arc4, and Arc7 ice classifications in Arctic waters. A navigability threshold of 95% RIO ≥ 0 was established to define navigable windows, and critical waters were identified where sections of the route remain in hazardous or risky conditions year-round. The results indicate that for No Ice Class vessels, Arc4 vessels, and Arc7 vessels, the navigable windows for westbound Route 1 and Route 2 under light, normal, and heavy ice conditions range from 70 to 133 days, 70 to 365 days, and 70 to 365 days, respectively, while for eastbound Route 3, the navigable windows range from 0 to 84 days, 0 to 238 days, and 7 to 365 days, respectively. The critical waters affecting the navigability of No Ice Class vessels, Arc4 vessels, and Arc7 vessels are primarily located in the Kara Sea, Laptev Sea and East Siberian Sea. This study, using the POLARIS methodology, provides valuable insights into the navigability of LNG carriers with different ice classes along the NSR, supporting the development and utilization of Arctic energy and shipping routes while offering decision-making support for stakeholders involved in Arctic maritime operations.
Deep learning, which is a dominating technique in artificial intelligence, has completely changed image understanding over the past decade. As a consequence, the sea ice extraction (SIE) problem has reached a new era. We present a comprehensive review of four important aspects of SIE, including algorithms, datasets, applications and future trends. Our review focuses on research published from 2016 to the present, with a specific focus on deep-learning-based approaches in the last five years. We divided all related algorithms into three categories, including the conventional image classification approach, the machine learning-based approach and deep-learning-based methods. We reviewed the accessible ice datasets including SAR-based datasets, the optical-based datasets and others. The applications are presented in four aspects including climate research, navigation, geographic information systems (GIS) production and others. This paper also provides insightful observations and inspiring future research directions.
Digital information on sea ice extent, thickness, volume, and distribution is crucial for understanding Earth's climate system. The Snow and Ice Mass Balance Apparatus (SIMBA) is used to determine snow and ice temperatures in Arctic, Antarctic, ice-covered seas, and boreal lakes. Snow depth and ice thickness are derived from SIMBA temperature regimes (SIMBA_ET and SIMBA_HT). In warm conditions, SIMBA_ET temperature-based ice thickness may have errors due to the isothermal vertical profile. SIMBA_HT provides a visible ice-bottom interface for manual quantification. We propose an unmanned approach, combining neural networks, wavelet analysis, and Kalman filtering (NWK), to mathematically establish NWK and retrieve ice bottoms from various SIMBA_HT datasets. In the Arctic, NWK-derived total thickness showed a bias range of −5.64 cm to 4.01 cm and a correlation coefficient of 95%−99%. For Baltic Sea ice, values ranged from 1.31 cm to 2.41 cm (88%−98% correlation), and for boreal lake ice, −0.7 cm to 2.6 cm (75%−83% correlation). During ice growth, thermal equilibrium, and melting, the bias varied from −3.93 cm to 2.37 cm, −1.92 cm to 0.04 cm, and −4.90 cm to 3.96 cm, with correlation coefficients of 76%−99%. These results demonstrate NWK's robustness in retrieving ice bottom evolution in different water environments.
Arctic summer sea ice has been declining in recent decades. In this study, we investigate the beginning of the Arctic melting season, i.e., sea ice melt onset (MO), in the Laptev Sea (LS) and East Siberian Sea (ESS) along the Northern Sea route. Three leading modes are identified by EOF decomposition, which we call the LE-mode, L-mode, and E-mode. In positive phases these modes exhibit earlier MO in the two seas, a seesaw-like structure in the southwest–northeast direction with earlier MO in the LS, or in the southeast–northwest direction with earlier MO in the ESS. The LE-mode, L-mode, and E-mode are closely related to the Arctic Oscillation (AO) in April, the Barents Oscillation (BO) in April, and the AO in May, respectively. When the AO in April is positive, a low pressure anomaly northwest of the LS and ESS brings warm, moist air masses from the lower latitudes toward the LS and ESS and causes earlier MO, corresponding to the positive LE-mode. When the BO in April is negative, a cyclonic anomaly around the Barents Sea tends to warm and moisten the LS and cause earlier MO there, corresponding to the positive L-mode. When AO in May is positive, a low pressure anomaly northeast of the LS and ESS brings more warm, moist air toward the ESS and causes earlier MO there, corresponding to the positive E-mode. In the 1980s, the negative LE-mode was prominent whereas in the early 1990s the positive LE-mode was dominant. Since the mid-1990s, the L-mode and E-mode have appeared more frequently.
This paper investigates the hub location problem arising in liner shipping, which is called liner shipping hub location problem. In contrast to most other hub location problems, many such problems in liner shipping have a special spatial structure where ships mainly follow certain main waterways, e.g., via the Suez Canal between Asia and Europe. In this paper, we utilize this spatial structure to propose three efficient mixed-integer linear programming (MILP) models for the liner shipping hub location problem, where we also explore the effect of the opening of the Arctic sea route on hub location. We further investigate the analytical properties of our proposed models. Numerical experiments are carried out to account for the effectiveness of our proposed models. As compared with the conventional hub location model, our proposed models can be solved by commercial MILP solvers, such as CPLEX, more efficiently.
Recent rapid environmental changes in Antarctica have often produced a sudden barrier to the marine animals. Adélie penguins, one of the top predators in the Antarctic ecosystem, are reported to confront the changes near the habitats by the appearance of large icebergs or drift ice. We tracked the foraging trips of Adélie penguins with GPS and time-depth recorders during the chick-guarding period in December 2018, at Adélie Cove in the Ross Sea, Antarctica, when 240 km² of a giant ice floe was approaching near the foraging areas. Here, we aimed to investigate how Adélie penguins respond to these natural obstacles. Our results showed that, among the 18 penguins, 4 individuals moved to the south of the Silverfish Bay fast ice and 14 moved further east beyond the large ice floe to the sparse drift ice. The 14 birds on the sparse ice either crossed (through the ice floe surface, n = 7) or bypassed (to the northern ice boundary, n = 2; to the southern ice boundary, n = 5). Compared to a neighboring population on Inexpressible Island, Adélie Cove penguins had a longer foraging trip duration and movement distance. Our results suggest that the giant ice floe could alter the foraging paths and penguins bypassed or crossed the ice to reach their foraging areas by spending more energy and time. For better understanding, further studies are required to estimate if penguins suffer from these changes.
The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for the rapidly changing Arctic-boreal region. Air quality in China, together with the long-range transport of atmospheric pollutants, was also indicated as one of the most crucial topics of the research agenda. These two geographical regions, the northern Eurasian Arctic-boreal region and China, especially the megacities in China, were identified as a “PEEX region”. It is also important to recognize that the PEEX geographical region is an area where science-based policy actions would have significant impacts on the global climate. This paper summarizes results obtained during the last 5 years in the northern Eurasian region, together with recent observations of the air quality in the urban environments in China, in the context of the PEEX programme. The main regions of interest are the Russian Arctic, northern Eurasian boreal forests (Siberia) and peatlands, and the megacities in China. We frame our analysis against research themes introduced in the PEEX Science Plan in 2015. We summarize recent progress towards an enhanced holistic understanding of the land–atmosphere–ocean systems feedbacks. We conclude that although the scientific knowledge in these regions has increased, the new results are in many cases insufficient, and there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures, especially the lack of coordinated, continuous and comprehensive in situ observations of the study region as well as integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, especially “the enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate climate change” and the “socio-economic development to tackle air quality issues”.
Arctic sea ice area and thickness have declined dramatically during the recent decades. Sea ice physical and mechanical properties become increasingly important. Traditional methods of studying ice mechanical parameters such as ice-coring cannot realize field test and long-term observation. A new principle of measuring mechanical properties of ice using ultrasonic was studied and an ultrasonic system was proposed to achieve automatic observation of ice mechanical parameters (Young’s modulus, shear modulus and bulk modulus). The ultrasonic system can measure the ultrasonic velocity through ice at different temperature, salinity and density of ice. When ambient temperature decreased from 0°C to −30°C, ultrasonic velocity and mechanical properties of ice increased, and vice versa. The shear modulus of the freshwater ice and sea ice varied from 2.098 GPa to 2.48 GPa and 2.927 GPa to 4.374 GPa, respectively. The bulk modulus of freshwater ice remained between 3.074 GPa and 4.566 GPa and the sea ice bulk modulus varied from 1.211 GPa to 3.089 GPa. The freshwater ice Young’s modulus kept between 5.156 GPa and 6.264 GPa and sea ice Young’s modulus varied from 3.793 GPa to 7.492 GPa. The results of ultrasonic measurement are consistent with previous studies and there is a consistent trend of mechanical modulus of ice between the process of ice temperature rising and falling. Finally, this ultrasonic method and the ultrasonic system will help to achieve the long-term observation of ice mechanical properties of ice and improve accuracy of sea ice models.
The ice resistance on ships in escort operations in level ice are investigated using the discrete element method (DEM). A dilated polyhedron—generated by the Minkowski sum of a sphere and a polyhedron—is employed in the DEM; this dilated polyhedron-based DEM (DPDEM) is adopted to simulate the ship–ice interaction, wherein the contact force and bond-failure criterion are considered for the collision and fracture of sea ice, respectively. A three-point bending test was simulated with DPDEM, and a field test was conducted in the Bohai Sea to validate the DEM results. Further, a parametric analysis of flexural strength was conducted to identify the parameters involved in the bond-failure criterion. The ice resistance on icebreakers and cargo ships in level ice are simulated using DPDEM. The simulated ice resistances are compared with the Lindqvist and Riska formulas and the model test, which proves the validity of the DEM simulation. The interaction between ships and level ice is simulated parametrically to investigate the ice resistance on cargo ships with and without the icebreaker escort. Influencing factors such as ship speed, ice thickness, and ship breadth were examined to investigate the ice resistance on the escorted cargo ship. Analysis and change rules of the ice resistance on cargos affected by those factors were given.
Purpose
Resilient route selection for oversized cargoes, one of the general bulk cargoes, has not been adequately optimized in terms of using the Arctic route. This study solves the problem of selecting the optimal shipping routes for oversized cargoes from Busan (South Korea) to Balkhash (Kazakhstan).
Design/methodology/approach
The study used the consistent fuzzy preference relation (CFPR) method, which is used to solve multi-criteria decision-making (MCDM) and uncertainty problems, to tackle the route selection. This method involves three procedures: first, the critical factors and alternative routes were obtained by the previous literature and an in-depth interview of experts of oversized cargo-handling with more than 20 years of working experience; second, the weightings for each critical factor were identified using the CFPR calculation process and third, alternative routes were evaluated using weighted critical factors.
Findings
The Northern Sea Route (NSR) combined with the inland waterways of Russia and Kazakhstan was first suggested for bulk carriers that handle oversized cargoes. The NSR could be a suitable route from Busan to Cape Kamenny of the Russian transshipment seaport, where oversized cargoes will be transferred to the river barge at Cape Kamenny, covering 4,913 km from the latter to Balkhash of Kazakhstan via the Ob/Irtysh River.
Practical implications
This study equips stakeholders in route selection for cargoes with strategies and methods to improve transportation efficiently and enhance shipping routes between Asia and the Commonwealth of Independent States (CIS). In addition to oversized cargoes, coal and timber from Russia can be transported to Asia using inland waterways and the NSR, which can also be used to transport plant equipment for petroleum refineries among Asian countries.
Originality/value
This is the first study to evaluate the suitability of the Artic route for oversized cargoes from South Korea to Kazakhstan. It provides a comprehensive evaluation framework of multimodal shipping routes and offers references for decision-makers when dealing with similar problems.
The sea ice conditions in the Kara Sea have important impacts on Arctic shipping, oil and gas production, and marine environmental changes. In this study, sea ice coverage (CR) less than 30% is considered as open water, its onset and end dates are defined as Topen and Tclose, respectively. The sea ice melt onset (Tmelt) is defined as the date when ice-sea freshwater flux initially changes from ice into the ocean. Satellite-based sea ice concentration (SIC) from 1989 to 2019 shows a negative correlation between Topen and Tclose (r = -0.77, p < 0.01) in the Kara Sea. This phenomenon is also obtained through analyzing the hindcast simulation from 1994 to 2015 by a coupled ocean and sea-ice model (NAPA1/4). The model results reveal that thermodynamics dominate the sea ice variations, and ice basal melt is greater than the ice surface melt. Heat budget estimation suggests that the heat flux is significant correlated with Topen (r = -0.95, p < 0.01) during the melt period (the duration of multi-year averaged Tmelt to Topen) influenced by the sea ice conditions. Additionally, this heat flux is also suggested to dominate the interannual variation of the heat input during the whole heat absorption process (r = 0.81, p < 0.01). The more heat input during this process leads to later Tclose (r = 0.77, p < 0.01). This is the physical basis of the negative correlation between Topen and Tclose. Therefore, the duration of open water can be predicted by Topen and thence support earlier planning of marine activities.
Quantification of the spatial variability and long‐term changes of Arctic sea ice motion is important for understanding the mechanisms of rapid Arctic sea ice decline because sea ice motion determines ice mass advection, outflow, thickness redistribution, as well as the formation of leads and ridges associated with ice deformation. The spatiotemporal changes in Arctic sea ice motion between 1979 and 2019 and their responses to atmospheric forcing were analysed using satellite‐derived sea ice motion products and atmospheric reanalysis data. The pan‐Arctic average sea ice drift speed increased significantly for all seasons between 1979 and 2019 (p < .001). Rates of increase were higher in autumn and winter than in spring and summer. Spatially, rates of increase in the peripheral seas in the Pacific sector—the Beaufort, Chukchi and East Siberian Seas—were higher than in the central Arctic Ocean and the peripheral seas in the Atlantic sector—the Kara and Laptev Seas. On the contrary, Arctic wind speed increased significantly only in autumn (p < .01). However, the correlation between wind speed and ice speed was the lowest in this season, suggesting that wind forcing is unable to completely account for drift speed increase. In general, the trends in above‐average drift speeds—retrieved from grid cells with the relatively high drift speeds—were statistically significant and were larger than that in average drift speeds probably because of enhanced response of ice motion to extreme wind forcing. The influence of the Arctic Oscillation, Beaufort High, and North Atlantic Oscillation on the zonal ice speed was symmetrical between the Pacific and Atlantic sectors of the Arctic Ocean, while the influence of the Dipole Anomaly and the east–west surface air pressure gradient in central Arctic on the meridional ice speed was distributed in an annular pattern and was the strongest along the Transpolar Drift Stream.
The Pan-Eurasian Experiment (PEEX) Science Plan, released in 2015, addressed a need for a holistic system understanding and outlined the most urgent research needs for sustainable development in the Artic-boreal region. Air quality in China and long-range transport of the atmospheric pollutants was also indicated as one of the most crucial topics of the research agenda. This paper summarizes results obtained during the last five years in the Northern Eurasian region. It also introduces recent observations on the air quality in the urban environments in China. The main regions of interest are the Russian Arctic, Northern Eurasian boreal forests (Siberia) and peatlands and on the mega cities in China. We frame our analysis against research themes introduced in 2015. We summarize recent progress in the understanding of the land – atmosphere – ocean systems feedbacks. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate-Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis. The fast-changing environment and ecosystem changes driven by climate change, socio-economic activities like the China Silk Road Initiative, and the global trends like urbanization further complicate such analyses. We recognize new topics with an increasing importance in the near future, such as enhancing biological sequestration capacity of greenhouse gases into forests and soils to mitigate the climate change and the socio-economic development to tackle air quality issues.
There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally-based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice los has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead-lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants, and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.
The International Association of Classification Societies (IACS), headquartered in London, is made up of ten classification societies such as Lloyds Register (LR), American Bureau of Shipping (ABS), Bureau Veritas (BV), China Classification Society (CCS), Det Norske Veritas (DNV), Germanischer Lloyd (GL), Korean Register (KR), Nippon Kaiji Kyokai (NK), Registro Italiano Navale (RINA), and the Russian Maritime Register of Shipping (RS), as well as the Indian Register of Shipping (IRS) as an associate member. The Council is the main governing body of the IACS and it meets annually to elect a Chairman and a Vice-Chairman for a one-year term, which rotates among IACS Members. The IACS is financed through membership fees and sale of publications. IACS plays a major role in transnational economic governance through its relationship with member classification societies to promote safety at sea. Keywords: American Bureau of Shipping (ABS); International Association of Classification Societies (IACS); transnational economic governance
The Satellite Application Facility (SAF) Ocean & Sea Ice project is organized by
EUMETSAT and a consortium of national meteorological centres lead by Meteo France. As a
pert of this the Norwegian and Danish Meteorological Institutes have developed and
implemented methods for automatic operational sea ice retrieval from satellite data. An
improved SSM/I sea ice concentration algorithm, and a new multi sensor method for
estimating sea ice coverage from SSM/I, scatterometer and AVHRR data has been developed
and tested. In the current paper the SAF Sea Ice products are presented with a brief description
of the methods and with some examples.
Arctic sea-ice extent (in summer) has been shrinking since the 1970s. However, we have little knowledge of the detailed spatial variability of this shrinking. In this study, we examine the (latitudinal) ice extent along each degree of longitude, using the monthly Arctic ice index data sets (1979-2012) from the National Snow and Ice Data Center. Statistical analysis suggests that: (1) for summer months (July-October), there was a 34-year declining trend in sea-ice extent at most regions, except for the Canadian Arctic Archipelago, Greenland and Svalbard, with retreat rates of 0.0562-0.0898 latitude degree/ year (or 6.26-10.00 km/year, at a significance level of 0.05); (2) for sea ice not geographically muted by the continental coastline in winter months (January-April), there was a declining trend of 0.0216-0.0559 latitude degree/year (2.40-6.22 km/year, at a significance level of 0.05). Regionally, the most evident sea-ice decline occurred in the Chukchi Sea from August to October, Baffin Bay and Greenland Sea from January to May, Barents Sea in most months, Kara Sea from July to August and Laptev Sea and eastern Siberian Sea in August and September. Trend analysis also indicates that: (1) the decline in summer ice extent became significant (at a 0.05 significance level) since 1999 and (2) winter ice extent showed a clear changing point (decline) around 2000, becoming statistically significant around 2005. The Pacific-Siberian sector of the Arctic accounted for most of the summer sea-ice decline, while the winter recovery of sea ice in the Atlantic sector tended to decrease.
In the summer of 2010, atmosphere–ice–ocean interaction was studied aboard the icebreaker R/V Xuelong during the Chinese National Arctic Research Expedition (CHINARE), in the sea ice zone of the Pacific Arctic sector between 150° W and 180° W up to 88.5° N. The expedition lasted from 21 July to 28 August and comprised of ice observations and measurements along the cruise track, 8 short-term stations and one 12-day drift station. Ship-based observations of ice thickness and concentration are compared with ice thickness measured by an electromagnetic induction device (EM31) mounted off the ship's side and ice concentrations obtained from AMSR-E. It is found that the modal thickness from ship-based visual observations matches well with the modal thickness from the mounted EM31. A grid of 8 profiles of ice thickness measurements (four repeats) was conducted at the 12-day drift station in the central Arctic (~ 86°50´ N–87°20´ N) and an average melt rate of 2 cm day−1, primarily bottom melt, was found. As compared with the 2005 data from the Healy/Oden Trans-Arctic Expedition (HOTRAX) for the same sector but ~ 20 days later (9 August to 10 September), the summer 2010 was first-year ice dominant (vs. the multi-year ice dominant in 2005), 70% or less in mean ice concentration (vs. 90% in 2005), and 94–114 cm in mean ice thickness (vs. 150 cm in 2005). Those changes suggest the continuation of ice thinning, less concentration, and younger ice for the summer sea ice in the sector since 2007 when a record minimum sea ice extent was observed. Overall, the measurements provide a valuable dataset of sea ice morphological properties over the Arctic Pacific Sector in summer 2010 and can be used as a benchmark for measurements of future changes.
There is an emerging need for regional applications of sea ice
projections to provide more accuracy and greater detail to scientists,
national, state and local planners, and other stakeholders. The present
study offers a prototype for a comprehensive, interdisciplinary study to
bridge observational data, climate model simulations, and user needs.
The study's first component is an observationally based evaluation of
Arctic sea ice trends during 1980-2008, with an emphasis on seasonal and
regional differences relative to the overall pan-Arctic trend. Regional
sea ice loss has varied, with a significantly larger decline of winter
maximum (January-March) extent in the Atlantic region than in other
sectors. A lead-lag regression analysis of Atlantic sea ice extent and
ocean temperatures indicates that reduced sea ice extent is associated
with increased Atlantic Ocean temperatures. Correlations between the two
variables are greater when ocean temperatures lag rather than lead sea
ice. The performance of 13 global climate models is evaluated using
three metrics to compare sea ice simulations with the observed record.
We rank models over the pan-Arctic domain and regional quadrants and
synthesize model performance across several different studies. The best
performing models project reduced ice cover across key access routes in
the Arctic through 2100, with a lengthening of seasons for marine
operations by 1-3 months. This assessment suggests that the Northwest
and Northeast Passages hold potential for enhanced marine access to the
Arctic in the future, including shipping and resource development
opportunities.
The recent Arctic winter sea ice retreat is most pronounced in the Barents Sea. Using available observations of the Atlantic inflow to the Barents Sea and results from a regional ice–ocean model the authors assess and quantify the role of inflowing heat anomalies on sea ice variability. The interannual variability and longer term decrease in sea ice area reflect the variability of the Atlantic inflow, both in observations and model simulations. During the last decade (1998–2008) the reduction in annual (July–June) sea ice area was 218 x 103 km2, or close to 50%. This reduction has occurred concurrent with an increase in observed Atlantic heat transport due to both strengthening and warming of the inflow. Modeled interannual variations in sea ice area between 1948 and 2007 are associated with anomalous heat transport (r= - 0.63) with a 70 x 103 km2 decrease per 10 TW input of heat. Based on the simulated ocean heat budget it is found that the heat transport into the western Barents Sea sets the boundary of the ice-free Atlantic domain and, hence, the sea ice extent. The regional heat content and heat loss to the atmosphere scale with the area of open ocean as a consequence. Recent sea ice loss is thus largely caused by an increasing ‘‘Atlantification’’ of the Barents Sea.
We present our best estimate of the thickness and volume of the Arctic Ocean ice cover from 10 Ice, Cloud, and land Elevation Satellite (ICESat) campaigns that span a 5-year period between 2003 and 2008. Derived ice drafts are consistently within 0.5 m of those from a submarine cruise in mid-November of 2005 and 4 years of ice draft profiles from moorings in the Chukchi and Beaufort seas. Along with a more than 42% decrease in multiyear (MY) ice coverage since 2005, there was a remarkable thinning of ∼0.6 m in MY ice thickness over 4 years. In contrast, the average thickness of the seasonal ice in midwinter (∼2 m), which covered more than two-thirds of the Arctic Ocean in 2007, exhibited a negligible trend. Average winter sea ice volume over the period, weighted by a loss of ∼3000 km3 between 2007 and 2008, was ∼14,000 km3. The total MY ice volume in the winter has experienced a net loss of 6300 km3 (>40%) in the 4 years since 2005, while the first-year ice cover gained volume owing to increased overall area coverage. The overall decline in volume and thickness are explained almost entirely by changes in the MY ice cover. Combined with a large decline in MY ice coverage over this short record, there is a reversal in the volumetric and areal contributions of the two ice types to the total volume and area of the Arctic Ocean ice cover. Seasonal ice, having surpassed that of MY ice in winter area coverage and volume, became the dominant ice type. It seems that the near-zero replenishment of the MY ice cover after the summers of 2005 and 2007, an imbalance in the cycle of replenishment and ice export, has played a significant role in the loss of Arctic sea ice volume over the ICESat record.
This paper identified an atmospheric circulation anomaly–dipole structure anomaly in the Arctic atmosphere and its relationship with winter sea ice motion, based on the International Arctic Buoy Program (IABP) dataset (1979–98) and datasets from the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) for the period 1960–2002. The dipole anomaly corresponds to the second-leading mode of EOF of monthly mean sea level pressure (SLP) north of 70°N during the winter season (October–March) and accounts for 13% of the variance. One of its two anomalous centers is stably occupied between the Kara Sea and Laptev Sea; the other is situated from the Canadian Archipelago through Greenland extending southeastward to the Nordic seas. The dipole anomaly differs from one described in other papers that can be attributed to an eastward shift of the center of action of the North Atlantic Oscillation. The finding shows that the dipole anomaly also differs from the “Barents Oscillation” revealed in a study by Skeie. Since the dipole anomaly shows a strong meridionality, it becomes an important mechanism to drive both anomalous sea ice exports out of the Arctic Basin and cold air outbreaks into the Barents Sea, the Nordic seas, and northern Europe.
When the dipole anomaly remains in its positive phase, that is, negative SLP anomalies appear between the Kara Sea and the Laptev Sea with concurrent positive SLP over from the Canadian Archipelago extending southeastward to Greenland, there are large-scale changes in the intensity and character of sea ice transport in the Arctic basin. The significant changes include a weakening of the Beaufort gyre, an increase in sea ice export out of the Arctic basin through Fram Strait and the northern Barents Sea, and enhanced sea ice import from the Laptev Sea and the East Siberian Sea into the Arctic basin. Consequently, more sea ice appears in the Greenland and the Barents Seas during the positive phase of the dipole anomaly. During the negative phase of the dipole anomaly, SLP anomalies show an opposite scenario in the Arctic Ocean and its marginal seas when compared to the positive phase, with the center of negative SLP anomalies over the Nordic seas. Correspondingly, sea ice exports decrease from the Arctic basin flowing into the Nordic seas and the northern Barents Sea because of the strengthened Beaufort gyre.
The finding indicates that influences of the dipole anomaly on winter sea ice motion are greater than that of the winter AO, particularly in the central Arctic basin and northward to Fram Strait, implying that effects of the dipole anomaly on sea ice export out of the Arctic basin become robust. The dipole anomaly is closely related to atmosphere–ice–ocean interactions that influence the Barents Sea sector.
Recent progress in sea ice concentration remote sensing by satellite microwave radiometers has been stimulated by two developments: First, the new sensor Advanced Microwave Scanning Radiometer-EOS (AMSR-E) offers spatial resolutions of approximately 6 × 4 km at 89 GHz, nearly 3 times the resolution of the standard sensor SSM/I at 85 GHz (15 × 13 km). Second, a new algorithm enables estimation of sea ice concentration from the channels near 90 GHz, despite the enhanced atmospheric influence in these channels. This allows full exploitation of their horizontal resolution, which is up to 4 times finer than that of the channels near 19 and 37 GHz, the frequencies used by the most widespread algorithms for sea ice retrieval, the NASA-Team and Bootstrap algorithms. The ASI algorithm used combines a model for retrieving the sea ice concentration from SSM/I 85-GHz data proposed by Svendsen et al. (1987) with an ocean mask derived from the 18-, 23-, and 37-GHz AMSR-E data using weather filters. During two ship campaigns, the correlation of ASI, NASA-Team 2, and Bootstrap algorithms ice concentrations with bridge observations were 0.80, 0.79, and 0.81, respectively. Systematic differences over the complete AMSR-E period (2002–2006) between ASI and NASA-Team 2 are below −2 ± 8.8%, and between ASI and Bootstrap are 1.7 ± 10.8%. Among the geophysical implications of the ASI algorithm are: (1) Its higher spatial resolution allows better estimation of crucial variables in numerical atmospheric and ocean models, for example, the heat flux between ocean and atmosphere, especially near coastlines and in polynyas. (2) It provides an additional time series of ice area and extent for climate studies.
1] We present a time series of sea ice extent in the Russian Arctic based on observational sea ice charts compiled by the Arctic and Antarctic Research Institute (AARI). These charts are perhaps the oldest operational sea ice data in existence and show that sea ice extent in the Russian Arctic has generally decreased since the beginning of the chart series in 1933. This retreat has not been continuous, however. For the Russian Arctic as a whole in summer, there have been two periods of retreat separated by a partial recovery between the mid-1950s and mid-1980s. The AARI charts, combined with air temperature records, suggest that the retreat in recent decades is pan-Arctic and year-round in some regions, whereas the early twentieth century retreat was only observed in summer in the Russian Arctic. The AARI ice charts indicate that a significant transition occurred in the Russian Arctic in the mid-1980s, when its sea ice cover began to retreat along with that of the rest of the Arctic. Summertime sea ice extents derived from the AARI data set agree with those derived from passive microwave, including the Hadley Centre's global sea ice coverage and sea surface temperature (HadISST) data set. The HadISST results do not indicate the 1980s transition or the partial recovery that took place before it. The AARI charts therefore add significantly to our understanding of the variability of Arctic sea ice over the last 8 decades, and we recommend their inclusion in future historical data sets of Arctic sea ice.
1] Recent record lows of Arctic summer sea ice extent are found to be triggered by the Arctic atmospheric Dipole Anomaly (DA) pattern. This local, second – leading mode of sea – level pressure (SLP) anomaly in the Arctic produced a strong meridional wind anomaly that drove more sea ice out of the Arctic Ocean from the western to the eastern Arctic into the northern Atlantic during the summers of 1995, 1999, 2002, 2005, and 2007. In the 2007 summer, the DA also enhanced anomalous oceanic heat flux into the Arctic Ocean via Bering Strait, which accelerated bottom and lateral melting of sea ice and amplified the ice– albedo feedback. A coupled ice – ocean model was used to confirm the historical record lows of summer sea ice extent. Citation: Wang, J., (2009), Is the Dipole Anomaly a major driver to record lows in Arctic summer sea ice extent?, Geophys. Res. Lett., 36, L05706, doi:10.1029/2008GL036706.
Recent Arctic sea ice retreat indicates that the Russian coastal seas encompassing the Northern Sea Route (NSR) will be among the first marine environments to transition to a summer ice-free state. Forty-six voyages carrying 1.26 million tons of cargo in 2012 suggest increasing economic viability of the NSR for eastward transport of natural resources from northern Norway and Russia. However, considerable uncertainty remains about the near-term length and variability of the navigation season, and shelf bathymetry presents a critical constraint limiting vessel draft and cargo capacity. This paper aims to quantify the length and variability of the NSR navigation season as constrained by both sea ice and bathymetry over the next 15 years. We present simulations of accessibility to the Russian maritime Arctic by Polar Class and nonice-strengthened vessels, as based on CCSM4 daily projections of sea ice concentration and thickness averaged for 2013–2027. Results indicate strong navigation uncertainties in the Kara, Laptev, and East Siberian Seas, while destinational shipping to the Barents and Chukchi Seas will be relatively unencumbered by ice. Shallow-draft ships may be required for maximum utilization of the navigation season for full NSR transits. This study can be viewed as support to strategic planning in identifying key navigational challenges and opportunities along the NSR.
Recent Arctic sea ice retreat indicates that the Russian coastal seas encompassing the Northern Sea Route (NSR) will be among the first marine environments to transition to a summer ice-free state. Forty-six voyages carrying 1.26 million tons of cargo in 2012 suggest increasing economic viability of the NSR for eastward transport of natural resources from northern Norway and Russia. However, considerable uncertainty remains about the near-term length and variability of the navigation season, and shelf bathymetry presents a critical constraint limiting vessel draft and cargo capacity. This paper aims to quantify the length and variability of the NSR navigation season as constrained by both sea ice and bathymetry over the next 15 years. We present simulations of accessibility to the Russian maritime Arctic by Polar Class and non-ice-strengthened vessels, as based on CCSM4 daily projections of sea ice concentration and thickness averaged for 2013–2027. Results indicate strong navigation uncertainties in the Kara, Laptev, and East Siberian Seas, while destinational shipping to the Barents and Chukchi Seas will be relatively unencumbered by ice. Shallow-draft ships may be required for maximum utilization of the navigation season for full NSR transits. This study can be viewed as support to strategic planning in identifying key navigational challenges and opportunities along the NSR.
Long-term trends in Arctic sea ice are of particular interest in studies of global temperature, climate change, and industrial application. This paper analyzes intra-annual and interannual trends in Ku-band backscatter over first-year (FY) and multiyear (MY) sea ice to develop a new sea-ice-type classification method. Histograms of backscatter are derived from high-resolution backscatter images created using the scatterometer image reconstruction (SIR) algorithm applied to measurements obtained by the SeaWinds instrument aboard QuikSCAT. The backscatter of FY and MY sea ice are clearly identifiable and are observed to vary seasonally. Using an average of the annual backscatter trends obtained from QuikSCAT, a classification of MY ice is obtained, which uses a time-dependent threshold value. Validation of the classification method is done using regional ice charts from the Canadian Ice Service. Differences in ice classification are found to be less than 6
for the winters of 2006–2007 and 2007–2008, and the end of 2008. Anomalies in the distribution of sea ice backscatter from year to year suggest a reduction in MY ice cover between 2003 and 2009 and an approximately equivalent increase in FY ice cover.
[1] The Arctic-wide melt season has lengthened at a rate of 5 days dec-1 from 1979 to 2013, dominated by later autumn freeze-up within the Kara, Laptev, East Siberian, Chukchi and Beaufort seas between 6 and 11 days dec-1. While melt onset trends are generally smaller, the timing of melt onset has a large influence on the total amount of solar energy absorbed during summer. The additional heat stored in the upper ocean of approximately 752 MJ m-2 during the last decade, increases sea surface temperatures by 0.5 to 1.5 °C and largely explains the observed delays in autumn freeze-up within the Arctic Ocean's adjacent seas. Cumulative anomalies in total absorbed solar radiation from May through September for the most recent pentad locally exceed 300-400 MJ m-2 in the Beaufort, Chukchi and East Siberian seas. This extra solar energy is equivalent to melting 0.97 to 1.3 m of ice during the summer.
[1] The extent of Arctic perennial sea ice, the year-round ice cover, was significantly reduced between March 2005 and March 2007 by 1.08 × 106 km2, a 23% loss from 4.69 × 106 km2 to 3.61 × 106 km2, as observed by the QuikSCAT/SeaWinds satellite scatterometer (QSCAT). Moreover, the buoy-based Drift-Age Model (DM) provided long-term trends in Arctic sea-ice age since the 1950s. Perennial-ice extent loss in March within the DM domain was noticeable after the 1960s, and the loss became more rapid in the 2000s when QSCAT observations were available to verify the model results. QSCAT data also revealed mechanisms contributing to the perennial-ice extent loss: ice compression toward the western Arctic, ice loading into the Transpolar Drift (TD) together with an acceleration of the TD carrying excessive ice out of Fram Strait, and ice export to Baffin Bay. Dynamic and thermodynamic effects appear to be combining to expedite the loss of perennial sea ice.
The seafloor has a profound role in Arctic Sea ice formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea ice on the ocean surface. Sea ice dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea ice together with buoy measurements are used to reveal the bathymetric control on sea ice growth and dynamics. Bathymetric effects on sea ice formation are clearly observed in the conformity between sea ice patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive regions of the sea ice cover across the Arctic Ocean. The large-scale conformity between bathymetry and patterns of different synoptic sea ice classes, including seasonal and perennial sea ice, is identified. An implication of the bathymetric influence is that the maximum extent of the total sea ice cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum ice extent has decreased drastically. Because of the geologic control, the sea ice cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea ice patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast, seasonal outlook, and decadal prediction of the sea ice cover. Moreover, the seafloor can indirectly influence the cloud cover by its control on sea ice distribution, which differentially modulates the latent heat flux through ice covered and open water areas.
The navigation distance via the Northern Sea Route (NSR) from a Northwest-European port to the Far East is approximately 40% shorter compared to the route via the Suez Canal. The shorter distance may facilitate more than a doubling of vessels’ operational energy efficiency performance. There is at present substantial uncertainty in schedule reliability via the NSR. Unless the schedule reliability is improved, the NSR should primarily be explored for bulk rather than for liner shipping. A major disadvantage with the NSR is its seasonality. Shipping operations in the summer time via the NSR may already today be profitable for minor bulk trades. Additional shipping routes may give more flexibility, and the NSR route choice option may facilitate supply chain agility and adaptability.
The seasonal melting of sea ice in the Arctic Ocean, which has been confirmed for several summers in a row and is widely documented, has become a hot topic in the media. It is fuelling many speculative scenarios about the purported renewal of a “cold war”, or even an actual armed conflict, in the Arctic, for the control of both its natural resources and its sea routes.The melting sea ice is indeed giving a second wind to projects, abandoned in the 19th century, to find shorter sea routes between Europe and Asia. A look at the map shows the savings in distance that can be achieved with the Arctic routes: for example, a trip between London and Yokohama through the Northwest Passage is 15,700km and 13,841km through the Northeast Passage, which is significantly shorter than the route through Suez (21,200km) or Panama (23,300km).2Data calculated by the author using Mapinfo GIS software.2 These findings fuel the idea that these Arctic routes, because they are shorter, are bound to attract abundant through traffic, and consequently will become a major political issue. Amid the media widespread image of a future maritime highway across Arctic seas, even some scientists yield to the popular image and assert, without proof, that Arctic traffic is set to increase rapidly.3For instance, «Because the Northwest Passage is about to become an alternative route to the Panama Canal, the volume of use within the passage will likely exceed 3000 vessels a year», Roston, 2009. The Northwest Passage’s Emergence as an International Highway. Southwestern Journal of International Law, 15, p. 469.3 Beyond the seemingly decisive advantage of Arctic routes, however, there remain many obstacles to navigation (Lasserre, 2010d). In addition, these scenarios for the development of marine traffic in the Arctic remain highly speculative and are not based on an analysis of shipowners’ perceptions, which is the goal of this paper.This article will thus present the results of an empirical survey conducted among shipping companies to determine their interest in developing activities in the Arctic. Besides examining the potential development of shipping in Arctic routes, this research must be replaced in the context of intense competition between shippers, competition that makes both service reliability and costs of transport paramount. In this competition structure, the benefits of established routes between major hubs seems to prevail, so that new routes have difficulty being established.
In September 2002, Arctic sea ice extent reached a minimum unprecedented in 24 years of satellite passive microwave observations, and almost certainly unmatched in 50 years of charting Arctic ice. Again, in September 2003, ice retreated to an unusually low extent, almost equaling the previous year's minimum. The Sea Ice Index (http://nsidc.org/data/seaice_index/), an easy-to-use source of information on sea ice trends and anomalies, assists in observing these minima. The Sea Ice Index is intended for both researchers and the scientifically inclined general public.
The extent of perennial sea ice in the East Arctic Ocean (0-180°E) decreased by nearly one half with an abrupt reduction of 0.95 × 106 km2, while the West Arctic Ocean (0-180°W) had a slight gain of 0.23 × 106 km2 between 2004 and 2005, as observed by satellite scatterometer data during November-December. The net decrease in the total perennial ice extent is 0.72 × 106 km2, about the size of Texas. Perennial ice in the East Arctic Ocean continued to be depleted with an areal reduction of 70% from October 2005 to April 2006. With the East Arctic Ocean dominated by seasonal sea ice, a strong summer melt may open a vast ice-free region with a possible record minimum ice extent largely confined to the West Arctic Ocean. Simultaneous scatterometer measurements of sea ice and winds will be crucial for sea ice monitoring and forecasts.
Data collected by the International Arctic Buoy Programme from 1979 to
1998 are analyzed to obtain statistics of sea level pressure (SLP) and
sea ice motion (SIM). The annual and seasonal mean fields agree with
those obtained in previous studies of Arctic climatology. The data show
a 3-hPa decrease in decadal mean SLP over the central Arctic Ocean
between 1979-88 and 1989-98. This decrease in SLP drives a cyclonic
trend in SIM, which resembles the structure of the Arctic Oscillation
(AO).Regression maps of SIM during the wintertime (January-March) AO
index show 1) an increase in ice advection away from the coast of the
East Siberian and Laptev Seas, which should have the effect of producing
more new thin ice in the coastal flaw leads; 2) a decrease in ice
advection from the western Arctic into the eastern Arctic; and 3) a
slight increase in ice advection out of the Arctic through Fram Strait.
Taken together, these changes suggest that at least part of the thinning
of sea ice recently observed over the Arctic Ocean can be attributed to
the trend in the AO toward the high-index polarity.Rigor et al. showed
that year-to-year variations in the wintertime AO imprint a distinctive
signature on surface air temperature (SAT) anomalies over the Arctic,
which is reflected in the spatial pattern of temperature change from the
1980s to the 1990s. Here it is shown that the memory of the wintertime
AO persists through most of the subsequent year: spring and autumn SAT
and summertime sea ice concentration are all strongly correlated with
the AO index for the previous winter. It is hypothesized that these
delayed responses reflect the dynamical influence of the AO on the
thickness of the wintertime sea ice, whose persistent `footprint' is
reflected in the heat fluxes during the subsequent spring, in the extent
of open water during the subsequent summer, and the heat liberated in
the freezing of the open water during the subsequent autumn.
In order to explore changes and trends in the timing of Arctic sea ice melt onset and freezeup, and therefore melt season length, we developed a method that obtains this information directly from satellite passive microwave data, creating a consistent data set from 1979 through present. We furthermore distinguish between early melt (the first day of the year when melt is detected) and the first day of continuous melt. A similar distinction is made for the freezeup. Using this method we analyze trends in melt onset and freezeup for 10 different Arctic regions. In all regions except for the Sea of Okhotsk, which shows a very slight and statistically insignificant positive trend (0.4 d decade-1), trends in melt onset are negative, i.e., toward earlier melt. The trends range from -1.0 d decade-1 for the Bering Sea to -7.3 d decade-1 for the East Greenland Sea. Except for the Sea of Okhotsk all areas also show a trend toward later autumn freeze onset. The Chukchi/Beaufort seas and Laptev/East Siberian seas observe the strongest trends with 7 d decade-1. For the entire Arctic, the melt season length has increased by about 20 days over the last 30 years. Largest trends of over 10 d decade-1 are seen for Hudson Bay, the East Greenland Sea, the Laptev/East Siberian seas, and the Chukchi/Beaufort seas. Those trends are statistically significant at the 99% level.
Analysis of a satellite-derived record of sea ice age for 1980 through March 2011 shows continued net decrease in multiyear ice coverage in the Arctic Ocean, with particularly extensive loss of the oldest ice types. The fraction of total ice extent made up of multiyear sea ice in March decreased from about 75% in the mid 1980s to 45% in 2011, while the proportion of the oldest ice declined from 50% of the multiyear ice pack to 10%. These losses in the oldest ice now extend into the central Arctic Ocean and adjacent to the Canadian Archipelago; areas where the ice cover was relatively stable prior to 2007 and where long-term survival of sea ice through summer is considered to be most likely. Following record-minimum multiyear ice coverage in summer 2008, the total multiyear ice extent has increased to amounts consistent with the negative trend from 2001-2006, with an increasing proportion of older ice types. This implies some ability for the ice pack to recover from extreme conditions. This recovery has been weakest in the Beaufort Sea and Canada Basin though, with multiyear ice coverage decreasing by 83% from 2002 to 2009 in the Canada Basin, and with more multiyear ice extent now lost in the Pacific sector than elsewhere in the Arctic Ocean.
Recent historic observed lows in Arctic sea ice extent, together with climate model projections of additional ice reductions in the future, have fueled speculations of potential new trans-Arctic shipping routes linking the Atlantic and Pacific Oceans. However, numerical studies of how projected geophysical changes in sea ice will realistically impact ship navigation are lacking. To address this deficiency, we analyze seven climate model projections of sea ice properties, assuming two different climate change scenarios [representative concentration pathways (RCPs) 4.5 and 8.5] and two vessel classes, to assess future changes in peak season (September) Arctic shipping potential. By midcentury, changing sea ice conditions enable expanded September navigability for common open-water ships crossing the Arctic along the Northern Sea Route over the Russian Federation, robust new routes for moderately ice-strengthened (Polar Class 6) ships over the North Pole, and new routes through the Northwest Passage for both vessel classes. Although numerous other nonclimatic factors also limit Arctic shipping potential, these findings have important economic, strategic, environmental, and governance implications for the region.
Satellite records show a decline in ice extent over more than three decades, with a record minimum in September 2012. Results from the Pan-Arctic Ice-Ocean Modelling and Assimilation system (PIOMAS) suggest that the decline in extent has been accompanied by a decline in volume, but this has not been confirmed by data. Using new data from the European Space Agency CryoSat-2 (CS-2) mission, validated with in situ data, we generate estimates of ice volume for the winters of 2010/11 and 2011/12. We compare these data with current estimates from PIOMAS and earlier (2003–8) estimates from the National Aeronautics and Space Administration ICESat mission. Between the ICESat and CryoSat-2 periods, the autumn volume declined by 4291 km3 and the winter volume by 1479 km3. This exceeds the decline in ice volume in the central Arctic from the PIOMAS model of 2644 km3 in the autumn, but is less than the 2091 km3 in winter, between the two time periods.
Starting with retrieved freeboards from four ICESat campaigns (ON05, October/November 2005; FM06, February/March 2006; ON06, October/November 2006; and MA07, March/April 2007) we estimate their ice thicknesses using constructed fields of daily snow depth and compare them with ice drafts from moored upward-looking sonars. The methodologies, considerations, and assumptions used in the conversion of freeboard to ice thickness are discussed. The thickness distributions of the Arctic multiyear and seasonal ice covers are contrasted. Broadly, the resulting fields seem seasonally and interannually consistent in terms of thickness, growth and ice production. We find mean thicknesses of 2.15/2.46 m in ON05/FM06 and an overall thinner ice cover of 1.96/2.37 m in ON06/MA07. This represents a growth of ∼0.3 m and ∼0.4 m during the ∼4-month intervals of the ON05-FM06 and ON06-MA07 campaigns, respectively. After accounting for data gaps, we compute overall Arctic Ocean ice volumes of 11,318, 14,075, 10,626, and 13,891 km3 for the ON05, FM06, ON06, and MA07 campaigns, respectively. The higher total volume in ON05 (versus ON06) can be attributed to the higher multiyear ice coverage that fall: 37% versus 31%. However, the higher estimated ice production (less export) during the second year (3265 versus 2757 km3) is likely due to the higher growth rate over the larger expanse of seasonal sea ice during the fall and winter. Inside a 25-km radius of two mooring locations in the Beaufort Sea, the estimated mean ICESat ice drafts from ON05 and FM06 are within 0.5 m of those measured at the moorings.
This paper describes the CryoSat satellite mission, due for launch in 2005, whose aim is to accurately determine the trends in Earth’s continental and marine ice fields. The paper’s purpose is to provide scientific users of the CryoSat data with a description of the design and operation of the SIRAL radar and the CryoSat platform, the data products, and the expected error budget. The ‘low-resolution mode’ (LRM), ‘synthetic aperture mode’ (SARM) and “synthetic aperture interferometric mode’ (SARInM) of the SIRAL radar are described, together with its system parameters, its antenna gain pattern and interferometer phase difference pattern, and its calibration modes. The orbit is described, together with the platform attitude and altitude control law and control systems, and the expected pointing and altitude knowledge. The geographical masks that are used to determine acquisitions in the three SIRAL modes are described. The SIRAL data products, and the processing applied to produce them, are described. Level 1b, level 2 and higher-level products are described in turn, with a particular emphasis on the new procedures applied to the SARInM and SARM processing over ice surfaces. The beam forming and multi-looking is summarised, and a description is given of the behaviour of the SARM and SARInM echoes over idealised surfaces. These inform descriptions of the elevation retrievals of the level 2 processing, including the SARInM retrieval of interferometric phase. The combination of these data, through cross-over analysis over continental ice sheets, and through averaging over sea-ice, to determine areal averages of ice sheet elevation change or sea-ice thickness, is described. The error budget in these higher-level products is described, together with its breakdown into errors arising from the instrument and errors arising from the retrievals. The importance of the co-variance of these errors in determining the final error is stressed. The description of the errors also includes a summary of the experiments required following the launch to validate the CryoSat mission data. An estimate of the mission performance over ice surfaces is made at various spatial scales, and it is concluded that even the relatively short, three-year duration of the CryoSat mission will allow it to make an important scientific contribution, particularly when combined with results from earlier satellite missions.
The Arctic Ocean has been greatly affected by climate change. Future predications show an even more drastic reduction of the ice cap which will open new areas for the exploration of natural resources and maritime transportation. Shipping through the Arctic Ocean via the Northern Sea Route (NSR) could save about 40% of the sailing distance from Asia (Yokohama) to Europe (Rotterdam) compared to the traditional route via the Suez Canal. However, a 40% reduction in distance using the NSR does not mean a corresponding 40% in cost savings due to many factors, including: higher building costs for ice-classed ships, non-regularity and slower speeds, navigation difficulties and greater risks, as well as the need for extra ice breaker service.The main purpose of this study is to investigate the economic potential of using the NSR as an alternative route between Asia and Europe by taking all the main factors into consideration. It focuses on economic aspect of the NSR, therefore navigation/ environmental/cultural/legal issues are not discussed.The economic study is conducted by a case study in which 4300 TEU container ships (both non-ice classed and ice classed) are employed to make year round service. The annual profit gained from regular service by a non-ice-classed ship via the Suez Canal for the entire year is compared to the annual profit gained from an ice-classed ship taking the NSR during the navigable months and Suez Canal for the rest of the year. There are three factors that influence the NSR the most: the navigable time of the NSR, Russian NSR fees and bunker prices. To make this study flexible, three scenarios for navigable time, three scenarios for Russian NSR fees as well as three scenarios for bunker prices are proposed. These assumptions are all combined with each other and the profit under each condition is then calculated. The overall comparison is made in order to see under which conditions the NSR is competitive with the Suez Canal.
A study of the sea ice concentrations obtained by passive microwave satellite imagery during the 1979–2007 period reveals remarkable changes in the sea ice cover of the Russian Arctic. A large reduction in the summer sea ice extent and area was observed in all Russian Arctic seas and straits while in the Barents Sea a significant decrease also took place in the winter months. Special attention was paid to the less studied length of the ice-free season, which was found to increase essentially everywhere, with particularly high rates of change in the Barents and Chukchi Seas.
An enhancement of the NASA Team sea ice concentration algorithm
overcomes the problem of a low ice concentration bias associated with
surface snow effects that are particularly apparent in Southern Ocean
sea ice retrievals. The algorithm has the same functional form as the
NASA Team algorithm, but uses a wider range of frequencies (19-85 GHz).
It accommodates ice temperature variability through the use of radiance
ratios as in the original NASA Team algorithm, and has the added
advantage of providing weather-corrected sea ice concentrations through
the utilization of a forward atmospheric radiative transfer model.
Retrievals of sea ice concentration with this new algorithm for both the
Arctic and Antarctic do not reveal the deficiencies present in either
the NASA Team or Bootstrap algorithms. Furthermore, quantitative
comparisons with infrared AVHRR data show that the enhanced algorithm
provides more accurate ice concentrations with much less bias than the
other two algorithms
NASA DAAC at the National Snow and Ice Data Center
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